Inconsistent satisfaction levels among readers of 'TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers.' While some appreciate the practical examples and clarity in instructions, others express disappointment due to outdated content, broken links, and the need for deeper explanations. The book is praised for being approachable yet criticized for lacking depth and relevance in light of recent TensorFlow Lite changes. Readers highlight the importance of addressing software and hardware updates to enhance usability and accuracy of information provided.
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Great book for data enthusiasts looking forward to explore new sources of data and interacting with the physical world.
Very entertaining style for. technical book. I enjoyed.
Tried using the first few links to download from GitHub and none of the links work. The book is worthless without being able to download the example excercises.
Looks like every git link in the code is removed, and entire Arduino code base is deleted
Mostly good and useful information probably would be better to remove the boilerplate code in the book and just point people to the relevant GitHub projects.
It has the right amount of details and combines theory and hands-on approach. I have totally enjoyed reading it, and looking forward to apply the gained knowledge to real applications.
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